Abdusshakur Olabisi

Key Skills

Software

Data Annotation Tech

CVAT

CrowdSource

iMerit

LabelImg

Mercor

Micro1

Roboflow

Top Subject Matter

CV & NLP Domain Expertise

image-to-text / text-to-image Domain Expertise

Text-to-speech / speech-to-text Domain Expertise

Top Data Types

Text

Image

Video

Top Task Types

Data Collection

Segmentation

Classification

Bounding Box

Object Detection

Text Generation

Question Answering

Text Summarization

Point/Key Point

Computer Programming/Coding

Function Calling

Prompt + Response Writing (SFT)

Evaluation/Rating

Fine-tuning

Freelancer Overview

AI Data Annotation Specialist. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Mindrift, Internal, and Proprietary Tooling. Education includes Bachelor of Science, Ahmadu Bello University (2021). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Data Collection.

Labeling Experience

AI Data Annotation Specialist

MindriftText

As an AI Data Annotation Specialist, I reviewed and corrected machine-generated audio transcriptions and labeled diverse data types including audio, videos, texts, and images. I ensured all annotations adhered to strict quality standards, applying detailed guidelines to maintain dataset consistency. I consistently identified and corrected errors, maintaining high accuracy and productivity across multiple data labeling platforms. • Labeled and reviewed multimodal data (text, audio, image, video) for NLP and computer vision tasks. • Applied rubric-based assessment to evaluate machine-generated outputs for TTS, STT, and OCR models. • Achieved high throughput and accuracy in labeling tasks across platforms such as Mindrift, iMerit, Crowdgen, Appen, and Prolific. • Ensured quality control and refined datasets used in AI model training.

As an AI Data Annotation Specialist, I reviewed and corrected machine-generated audio transcriptions and labeled diverse data types including audio, videos, texts, and images. I ensured all annotations adhered to strict quality standards, applying detailed guidelines to maintain dataset consistency. I consistently identified and corrected errors, maintaining high accuracy and productivity across multiple data labeling platforms. • Labeled and reviewed multimodal data (text, audio, image, video) for NLP and computer vision tasks. • Applied rubric-based assessment to evaluate machine-generated outputs for TTS, STT, and OCR models. • Achieved high throughput and accuracy in labeling tasks across platforms such as Mindrift, iMerit, Crowdgen, Appen, and Prolific. • Ensured quality control and refined datasets used in AI model training.

2023 - Present

Computer Vision & AI Engineer Intern

TextData Collection

I managed and automated data collection workflows for the African Voice Project, focusing on building African language datasets. I aggregated and processed multimodal data, including text, audio, image, and video, for use in STT and OCR AI model training. I maintained high quality control and ensured robust dataset consistency throughout the internship period. • Automated and tracked large-scale data collection via a Telegram-based tool (EqualyzAI). • Coordinated multilingual data curation and annotation workflows. • Achieved high transcription accuracy by enforcing annotation guidelines for STT and OCR models. • Filtered and processed data to support effective model training in the health data domain.

I managed and automated data collection workflows for the African Voice Project, focusing on building African language datasets. I aggregated and processed multimodal data, including text, audio, image, and video, for use in STT and OCR AI model training. I maintained high quality control and ensured robust dataset consistency throughout the internship period. • Automated and tracked large-scale data collection via a Telegram-based tool (EqualyzAI). • Coordinated multilingual data curation and annotation workflows. • Achieved high transcription accuracy by enforcing annotation guidelines for STT and OCR models. • Filtered and processed data to support effective model training in the health data domain.

2025 - 2025

Education

Work History